"""
Integration example: Extract identifiers from conversation files.

This demonstrates how to combine ConversationParser and IdentifierExtractor
to process conversation JSON files and extract institution identifiers.
"""

from pathlib import Path
from glam_extractor.parsers.conversation import ConversationParser
from glam_extractor.extractors.identifiers import IdentifierExtractor


def extract_identifiers_from_conversation(conversation_path: str | Path) -> dict:
    """
    Extract all identifiers from a conversation JSON file.
    
    Args:
        conversation_path: Path to conversation JSON file
    
    Returns:
        Dictionary with conversation metadata and extracted identifiers
    """
    # Parse conversation
    parser = ConversationParser()
    conversation = parser.parse_file(conversation_path)
    
    # Get conversation metadata
    metadata = parser.get_conversation_metadata(conversation)
    
    # Extract text from assistant messages (most likely to contain institution info)
    text = parser.extract_institutions_context(conversation)
    
    # Extract identifiers
    extractor = IdentifierExtractor()
    identifiers = extractor.extract_all(text, include_urls=True)
    
    # Group identifiers by scheme
    by_scheme = {}
    for identifier in identifiers:
        scheme = identifier.identifier_scheme
        if scheme not in by_scheme:
            by_scheme[scheme] = []
        by_scheme[scheme].append(identifier.identifier_value)
    
    return {
        "conversation": metadata,
        "identifiers": identifiers,
        "identifiers_by_scheme": by_scheme,
        "total_identifiers": len(identifiers),
    }


if __name__ == "__main__":
    # Example usage with the sample conversation
    sample_path = Path(__file__).parent.parent / "tests" / "fixtures" / "sample_conversation.json"
    
    if sample_path.exists():
        print("Processing sample conversation...")
        result = extract_identifiers_from_conversation(sample_path)
        
        print(f"\n=== Conversation: {result['conversation']['conversation_name']} ===")
        print(f"Messages: {result['conversation']['message_count']}")
        print(f"Total identifiers found: {result['total_identifiers']}\n")
        
        print("Identifiers by scheme:")
        for scheme, values in result['identifiers_by_scheme'].items():
            print(f"  {scheme}: {', '.join(values)}")
        
        print("\nDetailed identifiers:")
        for identifier in result['identifiers']:
            print(f"  - {identifier.identifier_scheme}: {identifier.identifier_value}")
            if identifier.identifier_url:
                print(f"    URL: {identifier.identifier_url}")
    else:
        print(f"Sample file not found at: {sample_path}")
        print("Please run from the project root directory.")